Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by
independent teams now outperform standard two-point estimators in terms of statistical …

We present a Bayesian velocity field reconstruction algorithm that performs the
reconstruction of the mass density field using only peculiar velocity data. Our method …

Field-level inference is emerging as a promising technique for optimally extracting
information from cosmological data sets. Previous analyses have shown field-based …

We update the field-level inference code karmma to enable tomographic forward-modeling
of shear maps. Our code assumes a log-normal prior on the convergence field, and properly …

We present a field-based signal extraction of weak lensing from noisy observations on the
curved and masked sky. We test the analysis on a simulated Euclid-like survey, using a …

We present miko, a catalog-to-cosmology pipeline for general flat-sky field-level inference,
which provides access to cosmological information beyond the two-point statistics. In the …

Traditionally, weak lensing cosmological surveys have been analyzed using summary
statistics motivated by their analytically tractable likelihoods, or by their ability to access …

Aims. We present the fully differentiable physical Differentiable Lensing Lightcone (DLL)
model, designed for use as a forward model in Bayesian inference algorithms that require …

We construct a field-based Bayesian Hierarchical Model for cosmic shear that includes, for
the first time, the important astrophysical systematics of intrinsic alignments and baryon …

We present GLASS, the Generator for Large Scale Structure, a new code for the simulation
of galaxy surveys for cosmology, which iteratively builds a light cone with matter, galaxies …